UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 4 Issue 3
March-2017
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR1703033


Registration ID:
170140

Page Number

153-155

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Title

Stock Market Prediction Using News Articles

Abstract

Stock market prediction involves the prediction of change of stock prices. It has its applications in finance and determining the state of the economy. In our work, we aim to demonstrate a way by which we can relatively accurately predict whether a stock’s price will increase or decrease on a day to day basis. This report describes our approach to make predictions from newspaper articles. We concentrate on two aspects: (1) Daily prediction of a stock’s price; and (2) A system which provides a relatively high return on investment using our prediction of stocks. This technique can be used to determine the impact of natural language when it comes to the stock market.

Key Words

NLP, Finance, Machine Learning

Cite This Article

"Stock Market Prediction Using News Articles", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.4, Issue 3, page no.153-155, March-2017, Available :http://www.jetir.org/papers/JETIR1703033.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Stock Market Prediction Using News Articles", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.4, Issue 3, page no. pp153-155, March-2017, Available at : http://www.jetir.org/papers/JETIR1703033.pdf

Publication Details

Published Paper ID: JETIR1703033
Registration ID: 170140
Published In: Volume 4 | Issue 3 | Year March-2017
DOI (Digital Object Identifier):
Page No: 153-155
Country: Bangalore, Karnataka, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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